Mid/Senior Data Engineer (Kraków/GCP)

Description

MID/SENIOR DATA ENGINEER – CAPCO POLAND

We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on innovative AI and automation initiatives for leading financial institutions.

At Capco Poland , we’re not just another consultancy – we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we help our clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management.

Our secret?

A culture that’s fast, flexible, and fiercely entrepreneurial. We move quickly, think creatively, and always put our people first.

We’re passionate about growth – both for our clients and ourselves – and that means attracting talented professionals who want to develop their skills, take ownership, and make a real impact.

We’re proud to be:

Trailblazers in banking, payments, capital markets, wealth, and asset management

Champions of an agile, nimble, and innovative work environment

Dedicated to building a team of talented professionals who share our drive and vision

Responsibilities

• We are looking for a strong Mid/Senior Data Engineer to join our growing data engineering team and contribute to building scalable, reliable data solutions for our financial services clients.
• You will work with modern data technologies and cloud platforms, developing and maintaining data pipelines, processing large datasets, and supporting the delivery of enterprise-scale data solutions.
• This is a great opportunity for a Data Engineer who already has hands-on commercial experience and wants to further develop their expertise in Python, Apache Spark, Hadoop, Linux, and Google Cloud Platform (GCP) while working on complex international projects.
• Design, develop, and maintain scalable data pipelines and data processing solutions.
• Develop data transformation and processing workflows using Python and Apache Spark .
• Work with large-scale datasets in distributed environments using Hadoop and related technologies .
• Build and support cloud-based data solutions on Google Cloud Platform (GCP) .
• Develop reliable ingestion processes integrating data from multiple source systems.
• Implement data transformations, validation rules, and data quality checks.
• Troubleshoot data pipeline issues and support performance optimization.
• Work with Linux-based environments , including scripting, deployment, and operational activities.
• Collaborate with Data Engineers, Architects, Analysts, and other project stakeholders to translate business requirements into technical solutions.
• Participate in code reviews and follow software engineering and data engineering best practices.
• Create and maintain technical documentation covering data flows, dependencies, configurations, and operational procedures.
• Support deployment, testing, stabilization, and ongoing maintenance of data solutions.

Requirements

• 4-6+ years of commercial experience in Data Engineering or a similar role.
• Good hands-on programming skills in Python .
• Practical experience with Apache Spark , including building and maintaining data processing jobs.
• Experience working with Hadoop or distributed data processing ecosystems.
• Good knowledge of Linux and command-line environments.
• Commercial experience with Google Cloud Platform (GCP) and relevant data services.
• Good understanding of ETL/ELT processes, data pipelines, and data transformation concepts .
• Working knowledge of SQL and relational data concepts.
• Understanding of data quality, monitoring, and troubleshooting practices.
• Familiarity with Git and modern software development practices.
• Ability to work effectively in an Agile environment and collaborate with distributed teams.
• Good communication skills and English at a minimum B2 level .
• Experience with GCP services such as BigQuery, Cloud Storage, Dataproc, Dataflow, or Pub/Sub .
• Experience in Financial/Banking domain
• Experience with orchestration tools such as Apache Airflow .
• Familiarity with CI/CD processes for data solutions.
• Knowledge of data modelling and data warehouse concepts.
• Experience working with financial services or banking clients.
• Familiarity with containerization technologies such as Docker or Kubernetes.
• ONLINE RECRUITMENT PROCESS
• Screening call with the Recruiter
• Hiring Manager Technical Interview
• Client Interview
• Feedback / Offer
• LI-HYBRID